https://github.com/mzohaib364/movie-recommedation-system-based-on-scraped-data

https://github.com/mzohaib364/movie-recommedation-system-based-on-scraped-data

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• Host: GitHub
• URL: https://github.com/mzohaib364/movie-recommedation-system-based-on-scraped-data
• Owner: MZohaib364
• Created: 2024-05-15T07:16:28.000Z (8 months ago)
• Default Branch: main
• Last Pushed: 2024-08-21T16:20:32.000Z (5 months ago)
• Last Synced: 2024-08-21T18:24:21.622Z (5 months ago)
• Language: Jupyter Notebook
• Size: 56.6 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Movie-Recommedation-System-based-on-scraped-data

Movie Recommendation System

Overview:

        This project implements a basic movie recommendation system that scrapes data from the IMDb website. It retrieves information from the Most Popular Movies page on IMDb, including movie titles, runtime, rating, age restriction, genre, writer(s), director(s), and fun movie trivia. The scraped data is stored in a Pandas dataframe.

Features:

> Scrapes data from IMDb Most Popular Movies page.

> Stores data in a Pandas dataframe.

> Allows users to specify preferences for genre, minimum rating, maximum runtime, and age restriction.

> Filters the dataframe based on user preferences.

> Recommends a movie based on the user's criteria, displaying title, writer, director, and trivia.

> If no movies match the user's preferences, recommends any movie from the original dataframe.

Usage:

> Run the program.

> Enter preferences for genre, minimum rating, maximum runtime, and age restriction when prompted.

> Receive a movie recommendation based on your preferences.

Technologies Used:

> Python

> Selenium for web scraping

> Pandas for data manipulation

How to Run:

> Clone this repository to your local machine.

> Install the required dependencies.

> Run the main script.